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SHAMAN is a SHiny application for Metagenomic ANalysis including the normalization,
the differential analysis and mutiple visualization.

SHAMAN is based on DESeq2 R package
[Anders and Huber 2010]
for the analysis of metagenomic data, as suggested in
[McMurdie and Holmes 2014,Jonsson2016]
. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2
[Love 2014]
.
Resulting p-values are adjusted according to the Benjamini and Hochberg procedure [Benjamini and Hochberg 1995].
The PCOA is performed with the
ade4 R package
and plots are generated with
ggplot2
or
D3.js packages
.
A presentation about SHAMAN is available
here
and a poster
here.
SHAMAN is compatible with standard formats for metagenomic analysis. We also provide a complete pipeline for OTU picking and annotation named
MASQUE
used in production at Institut Pasteur.

If you have any comments, questions or suggestions, or need help to use SHAMAN, please contact us at
shaman@pasteur.fr
and please provide us with enough information that we can recreate the problem. Useful things to include are:

Input data (or examples, a small test case sufficient to recreate the problem)

Information about which system your are using: web version, docker or R installation

What's new in SHAMAN

April 17th 2018 - Bioinformatics

The bioinformatic treatment offers a larger access to parameters. We also worked a lot on the documentation.

September 4th 2017 - Bioinformatics

The bioinformatic treatment of fastq reads is now available in SHAMAN. For now, SHAMAN allows to compute OTU, build an OTU table and annotate them with the last version of the available database. This application is for 16S/18S/23S/28S/ITS sequencing.

July 18th 2017 - Normalization and visualisation

A new method for normalization called total counts was added. More options have been added to the abundance tree.

May 30th 2017 - Bug fixes

Some visualization bug with the abundance tree and phylogenetic tree are now fixed. The export of the relative abundance and normalised abundance are now given in the right level. This update prepares the field for the next major release of shaman for June.

March 30th 2017 - Krona, Phylogeny and bug fixes

Krona and phylogenetic tree plots are now available in visualisation. Several new distance are available in PCOA. The import float count matrices is now ok. We have finaly debugged the export of the relative abundance/normalized matrices.

Dec 9th 2016 - Phylogenetic tree and stress plot

You can now upload a phylogenetic tree to calculate the unifrac distance (only available at the OTU level).
The stress plot has been added to evaluate the goodness of fit of the NMDS.

Nov 22th 2016 - New visualization and bug fix

We have implemented a new visualization called tree abundance. Some bugs have been fixed (thanks Carine Rey from ENS).

Oct 12th 2016 - Filtering step and bugs fix

You can now apply a filter on the features according to their abundance
and the number of samples. Bugs on confidence intervals for the alpha diversity have been fixed.

Sep 21th 2016 - SHAMAN on docker

The install of SHAMAN is now available with docker.
The R install is also updated and passed in release candidate state.

Sep 14th 2016 - Download and install SHAMAN

You can install SHAMAN (beta).

Sep 9th 2016 - PCA/PCOA

You can select the axes for the PCOA and PCA plots.

Aug 1st 2016 - Biom format

SHAMAN can now support all the Biom format versions.

Jun 24th 2016 - Comparisons plots

The venn diagram and the heatmap of foldchange
have been added to compare the results of 2 or more contrasts.

Jun 17th 2016 - Diversity plots

Enhancement of the visualtisation of the diverties.
The shanon and inv. shanon have been added.

Two groups of person follow two strict diet periods that involve the intake of 40g following 10g of fiber per day, or 10g of fiber after a 40g fiber intake period:

The 16S rRNA (V3 - V4 regions) from fece samples was sequenced at time stamp : 2, 3, 4 and 5.
The analysis will consider the different impact of the different fiber intake and the comparison to patient metabolic data.

The first step consists to load the count table and the annotation table as follow :

'Tables' section provides the results of the differential analysis.
For one given contrast, we have:
- The id of the given taxonomical level
- The base mean is the mean normalized count for the given annotation of all samples.
- The fold-change is a mesure describing how much the abundance varies from one condition to an other. For instance, if the abundance is 100 in condition 1 and 200 for condition 2, the fold-change equals 100/200=0.5.
- The log2 fold-change is the log2 value of the fold-change.
- The p-value adjusted (padj) is the pvalue obtained by the Wald test and adjusted by Benjamini & Hochberg procedure (BH) or Benjamini & Yekutieli procedure (see linear model options).

'Diagnostic plots' section provides several visualization to control the analysis
- Barplot